Magnetic Resonance Imaging (MRI) is an imaging technique based in part on the absorption and emission of energy in the radio frequency range. To obtain the necessary magnetic resonance (MR) images, a patient (or other target) is placed in a magnetic resonance scanner. The scanner provides a magnetic field that causes magnetic moments in the patient or target atoms to align with the magnetic field. The scanner also includes coils that apply a transverse magnetic field. RF pulses are emitted by the coils, causing the target atoms to absorb energy. In response to the RF pulses, photons are emitted by the target atoms and detected as signals in receiver coils.
The signals detected in the receiver coils may be processed to construct an image of the target. The signals may be made proportional to the spatial frequency content (k-space) of the image through the proper application of gradients to the magnetic field. The k-space may comprise sets of samples, called lines, each line corresponding to a single phase encoding of the sampling process. It is well known that the number and spacing of lines in k-space determines both the field of view (FOV) and the spatial resolution of the reconstructed image.
Data processing may be performed on the k-space samples to produce a final image of the object in “image space”, e.g. a spatial arrangement of pixels. The data processing is typically performed using a computer, which is any device comprising a processor and memory, wherein the processor executes instructions and acts upon data provided from the memory.
Rapid imaging is desirable in order to reduce the time required to perform volume imaging consisting of a large number of slices, to reduce the breath-hold time, or for dynamic imaging applications such as functional imaging of the heart or brain. Rapid imaging also provides increased motion tolerance. A number of accelerated imaging methods have been developed. In several of these methods, undesirable “ghost” artifacts arise when the k-space samples are processed into the image domain. In one such method, known as echo-planar imaging (EPI), distortions in k-space may lead to image domain ghosts. In another such method, known as SENSE, intentional k-space undersampling (sampling fewer lines than the number required to image a chosen field-of-view) accelerates the data acquisition but results in image domain ghosts due to aliasing. For more details on SENSE see Pruessmann et al., SENSE: Sensitivity Encoding for Fast MRI, Magnetic Resonance in Medicine, 1999 Nov; 42(5): 952–962.) With the SENSE approach, ghost artifacts which arise from aliasing may be suppressed in the image by way of a technique known as “phased array combining”. Phased array combining may be applied to suppress ghost artifacts arising from a variety of mechanisms, not just aliasing. U.S. patent application Ser. No. 09/825,617, entitled Ghost Artifact Cancellation Using Phased Array Processing, and filed on Apr. 3, 2001, by Kellman et al. (henceforth “Kellman 1”), teaches one such phased array combining approach.
Phased array combining approaches for ghost cancellation (including SENSE) involve combining multiple intermediate images, each comprising ghost artifacts, to produce a final image in which ghost artifacts are suppressed. Often, the intermediate images are combined in a manner which is numerically ill-conditioned, so that noise in the intermediate images as well as errors in the combining weights (brought on, for instance, by noise in the operation and characterization of the signal reception process) may amplify noise in the final image. One technique to mitigate this problem is called regularization or matrix conditioning. Regularization involves a tradeoff between a level of ghost artifact suppression and noise amplification. Current approaches apply a fixed amount of regularization to all pixels of an image. Such approaches do not take into account that particular regions (sets of one or more pixels) of the final image may benefit from substantially less ghost suppression than others, and therefore can benefit from greater noise reduction by trading off more ghost suppression than in other regions of the image.